Background: Maxillary sinus although shows normal anatomical variations and it is important to know about them. Evaluating maxillary sinus and identifying its variations on Computed Tomography not only detects the different variations but also helps in planning and guiding Various Sinus Surgery and preventing possible complications. Purpose: Aim of this study was to detect anatomical variations of maxillary sinuses in patients using Multi-detector Computed Tomography. Materials and Methods: Paranasal sinuses of 130 patients who were subjected to Computerised Tomography of Paranasal Sinus with CT (Seimens 128 slice Somatom Perspective) machine were studied. Results: A total PNS Para Nasal Sinuses of total 130 patients were studied. Out of which only 36 patients had maxillary sinu variations. Among accessory ostia of maxillary sinus was the commonest anatomical variation and was seen in 23 (18%) of cases. Hyperpneumatization of maxillary sinus was detected in 7cases (5%) and Antral septa were found in 13 cases (10%). Conclusion: Thus, it's important to accurately assess the maxillary sinus on Computed Tomography and to determine the various anatomical variations of the same so as to differentiate pathological lesions from an anatomical variation and avoiding unnecessary surgical explorations and complications.
INTRODUCTIONKnee pain is one of the common disability with which the patients often presents to the clinicians. The knee joint is one of the most important weight bearing joint of our body which consists of carious ligaments for stabilizing the joint for its functioning. Of the many ligaments of the knee joint ACL is one of the most commonly injured ligament. MRI gives us an excellent idea about the normal anatomy and injuries of ACL. There is great impact on the diagnosis and management of ACL injuries after the MR evaluation.1 Thus the use of MRI as first line investigation in suspected ACL injuries can avoid large number of unnecessary diagnostic arthroscopies. The clinical examination has its limits in case of acute injury with pain or swelling and also with associated meniscal tear and chondral injury limiting their sensitivity and specificity.2 MRI is highly accurate for diagnosing ACL tears with accuracy, sensitivity and specificity of more than 90%.3,4 The spectrum of MRI also gives us appropriate information regarding the injuries to the associated ligaments around knee joint and helps in planning the arthroscopic and nonarthroscopic surgery. This article emphasizes on information regarding the normal ACL anatomy and ACL tears with imaging features for diagnosing ACL tears, chronic tear and mucoid degeneration. The aim and objective of this work was to study the MRI features of complete and partial ACL tear and to study the MRI features of chronic tear and degeneration of ACL. ABSTRACTBackground: Of all the ligaments of the knee joint the Anterior cruciate ligament (ACL) is the most commonly injured. It is an important pillar of the ligament stabilization of knee joint preventing anterior translation of Tibia over Fibula. Magnetic resonance imaging (MRI) is an excellent modality providing fine-resolution and multiplanar imaging without any radiation, for detection and evaluation of ACL injury with the associated injuries to other ligaments of the knee join. The purpose of the work was to study the role of MRI in classifying the ACL injuries. Methods: MRI Knee of 162 patients with ACL injuries was studied. All the MR imaging scans were performed on 1.5-T MR system (Siemens magnetom Essenza). Results: A total of 162 patients were studied in which majority of them i.e. 43 patients had interstitial sprain, 38 patients had complete tear, 33 patients had mucoid degeneration, 27 had partial tear and 14 had high grade partial tear, however 7 patients had normal ACL. There were associated injuries to the other ligaments of the knee joint along with ACL injury, medial meniscus tear being the most common and was seen in 39.50% followed by lateral meniscus tear in 9.87%, MCL tear in 6.79%, LCL tear in 1.85% and PCL tear in 2.46 %. Conclusions: MRI is a good modality for classifying ACL injury and evaluation of injuries to the associated ligaments.
Background and Objective: Knee joint is the complex joint. It is much frequently injured joint due to trauma. The principle intra articular structures in the knee are the 2 cruciate ligaments, 2 menisci and the 2 collateral ligaments. The main objective is to study the MRI findings in ligament injuries of knee joint. Materials and Methods: MRI knee of 110 patients with suspected ligament injuries of knee joint was performed on 1.5-T MR system using flexible surface knee coil. Results: A total of 110 patients in a period of 2 years were collected and analysed comprising of either single ligament or combination of ligament tears. Anterior Cruciate Ligament (ACL) tear was most common and seen in 61 patients followed by Medial Collateral Ligament (MCL) in 31, Lateral Collateral Ligament (LCL) in 22 and Posterior Cruciate Ligament (PCL) in 16 patients. Majority of the patients belonged to age group 18-30 years with right knee involvement. Males dominated in this study constituting 63.64% of total population. Conclusion: MRI is non-invasive prime imaging modality with nonionizing radiation and multi planar capabilities. It accurately detects, localizes and characterizes various ligament injuries of the knee joint and help in arriving at accurate final diagnosis thereby guiding further management of the patient.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.